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Robust firm pricing with panel data

  • Handel, Benjamin R.
  • Misra, Kanishka
  • Roberts, James W.
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    Firms often have imperfect information about demand for their products. We develop an integrated econometric and theoretical framework to model firm demand assessment and subsequent pricing decisions with limited information. We introduce a panel data discrete choice model whose realistic assumptions about consumer behavior deliver partially identified preferences and thus generate ambiguity in the firm pricing problem. We use the minimax-regret criterion as a decision-making rule for firms facing this ambiguity. We illustrate the framework’s benefits relative to the most common discrete choice analysis approach through simulations and empirical examples with field data.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0304407613000420
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    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 174 (2013)
    Issue (Month): 2 ()
    Pages: 165-185

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    Handle: RePEc:eee:econom:v:174:y:2013:i:2:p:165-185
    DOI: 10.1016/j.jeconom.2013.02.007
    Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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    1. Makoto Abe, 1995. "A Nonparametric Density Estimation Method for Brand Choice Using Scanner Data," Marketing Science, INFORMS, vol. 14(3), pages 300-325.
    2. Richard Blundell & Martin Browning & Ian Crawford, 2002. "Nonparametric Engel Curves and Revealed Preference," CAM Working Papers 2002-04, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    3. Bergemann, Dirk & Schlag, Karl, 2011. "Robust monopoly pricing," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2527-2543.
    4. Michael P. Keane & Robert M. Sauer, 2009. "Classification Error in Dynamic Discrete Choice Models: Implications for Female Labor Supply Behavior," Econometrica, Econometric Society, vol. 77(3), pages 975-991, 05.
    5. Sauer, Robert & Keane, Michael P., 2007. "A computationally practical simulation estimation algorithm for dynamic panel data models with unobserved endogenous state variables," Discussion Paper Series In Economics And Econometrics 0705, Economics Division, School of Social Sciences, University of Southampton.
    6. Dirk Bergemann & Karl H. Schlag, 2008. "Pricing without Priors," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 560-569, 04-05.
    7. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March.
    8. Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
    9. Richard Blundell & Martin Browning & Ian Crawford, 2008. "Best Nonparametric Bounds on Demand Responses," Econometrica, Econometric Society, vol. 76(6), pages 1227-1262, November.
    10. Dirk Bergemann & Stephen Morris, 2003. "Robust Mechanism Design," Levine's Bibliography 666156000000000035, UCLA Department of Economics.
    11. Varian, Hal R, 1982. "The Nonparametric Approach to Demand Analysis," Econometrica, Econometric Society, vol. 50(4), pages 945-73, July.
    12. Tülin Erdem & Susumu Imai & Michael Keane, 2003. "Brand and Quantity Choice Dynamics Under Price Uncertainty," Quantitative Marketing and Economics (QME), Springer, vol. 1(1), pages 5-64, March.
    13. Erdem, Tulin & Keane, Michael P. & Sun, Baohong, 1998. "Missing price and coupon availability data in scanner panels: Correcting for the self-selection bias in choice model parameters," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 177-196, November.
    14. Keane, Michael P, 1997. "Modeling Heterogeneity and State Dependence in Consumer Choice Behavior," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 310-27, July.
    15. Hal R. Varian, 1983. "Non-parametric Tests of Consumer Behaviour," Review of Economic Studies, Oxford University Press, vol. 50(1), pages 99-110.
    16. Itzhak Gilboa & David Schmeidler, 1989. "Maxmin Expected Utility with Non-Unique Prior," Post-Print hal-00753237, HAL.
    17. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    18. Steven T. Berry & Philip A. Haile, 2009. "Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers," Cowles Foundation Discussion Papers 1718, Cowles Foundation for Research in Economics, Yale University, revised Mar 2010.
    19. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132.
    20. Charles F. Manski, 2007. "Partial Identification Of Counterfactual Choice Probabilities," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1393-1410, November.
    21. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    22. Geweke, John, 2012. "Nonparametric Bayesian modelling of monotone preferences for discrete choice experiments," Journal of Econometrics, Elsevier, vol. 171(2), pages 185-204.
    23. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    24. Bart J. Bronnenberg & Michael W. Kruger & Carl F. Mela, 2008. "—The IRI Marketing Data Set," Marketing Science, INFORMS, vol. 27(4), pages 745-748, 07-08.
    25. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-90, July.
    26. Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
    27. Liran Einav & Ephraim Leibtag & Aviv Nevo, 2010. "Recording discrepancies in Nielsen Homescan data: Are they present and do they matter?," Quantitative Marketing and Economics (QME), Springer, vol. 8(2), pages 207-239, June.
    28. Matzkin, Rosa L., 1993. "Nonparametric identification and estimation of polychotomous choice models," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 137-168, July.
    29. Igal Hendel & Aviv Nevo, 2005. "Measuring the Implications of Sales and Consumer Inventory Behavior," NBER Working Papers 11307, National Bureau of Economic Research, Inc.
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